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        MultiQC: Summarize analysis results for multiple tools and samples in a single report
        Philip Ewels, Måns Magnusson, Sverker Lundin and Max Käller
        Bioinformatics (2016)
        doi: 10.1093/bioinformatics/btw354
        PMID: 27312411

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        About MultiQC

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        MultiQC is published in Bioinformatics:

        MultiQC: Summarize analysis results for multiple tools and samples in a single report
        Philip Ewels, Måns Magnusson, Sverker Lundin and Max Käller
        Bioinformatics (2016)
        doi: 10.1093/bioinformatics/btw354
        PMID: 27312411

        A modular tool to aggregate results from bioinformatics analyses across many samples into a single report.

        Report generated on 2023-05-12, 11:59 CEST based on data in:

        General Statistics

        Showing 256/256 rows and 3/6 columns.
        Sample Name% Dups% GCM Seqs
        BEB01_qc_fHP_1
        32.8%
        49%
        25.6
        BEB01_qc_fHP_2
        36.0%
        49%
        25.6
        BEB02_qc_fHP_1
        32.1%
        45%
        22.3
        BEB02_qc_fHP_2
        32.7%
        45%
        22.3
        BEB03_qc_fHP_1
        17.3%
        48%
        26.6
        BEB03_qc_fHP_2
        18.2%
        48%
        26.6
        BEB04_qc_fHP_1
        16.8%
        48%
        22.7
        BEB04_qc_fHP_2
        17.5%
        48%
        22.7
        BEB05_qc_fHP_1
        17.7%
        49%
        27.5
        BEB05_qc_fHP_2
        19.5%
        49%
        27.5
        BEB10_qc_fHP_1
        18.1%
        55%
        22.3
        BEB10_qc_fHP_2
        23.2%
        55%
        22.3
        BEB11_qc_fHP_1
        19.1%
        51%
        24.1
        BEB11_qc_fHP_2
        24.7%
        51%
        24.1
        BEB13_qc_fHP_1
        16.2%
        46%
        19.5
        BEB13_qc_fHP_2
        17.4%
        46%
        19.5
        BEB15_qc_fHP_1
        16.2%
        45%
        21.4
        BEB15_qc_fHP_2
        17.8%
        45%
        21.4
        BEB16_qc_fHP_1
        23.4%
        44%
        22.1
        BEB16_qc_fHP_2
        25.2%
        44%
        22.1
        BEB18_qc_fHP_1
        16.6%
        46%
        16.6
        BEB18_qc_fHP_2
        18.0%
        46%
        16.6
        BEB19_qc_fHP_1
        21.9%
        45%
        22.9
        BEB19_qc_fHP_2
        24.6%
        45%
        22.9
        BEB21_qc_fHP_1
        23.1%
        43%
        22.7
        BEB21_qc_fHP_2
        25.7%
        43%
        22.7
        BEB22_qc_fHP_1
        17.0%
        44%
        22.2
        BEB22_qc_fHP_2
        19.7%
        44%
        22.2
        BEB23_qc_fHP_1
        31.8%
        44%
        22.6
        BEB23_qc_fHP_2
        35.0%
        44%
        22.6
        BEB25_qc_fHP_1
        10.1%
        46%
        15.7
        BEB25_qc_fHP_2
        11.8%
        46%
        15.7
        BEB27_qc_fHP_1
        24.3%
        52%
        21.1
        BEB27_qc_fHP_2
        26.8%
        52%
        21.1
        BEB28_qc_fHP_1
        19.5%
        48%
        21.7
        BEB28_qc_fHP_2
        21.0%
        48%
        21.7
        BEB29_qc_fHP_1
        24.9%
        52%
        22.2
        BEB29_qc_fHP_2
        27.4%
        52%
        22.2
        BEB30_qc_fHP_1
        26.6%
        50%
        22.9
        BEB30_qc_fHP_2
        30.1%
        50%
        22.9
        BEB31_qc_fHP_1
        18.4%
        46%
        22.8
        BEB31_qc_fHP_2
        20.6%
        46%
        22.8
        BEB32_qc_fHP_1
        31.2%
        45%
        25.7
        BEB32_qc_fHP_2
        35.1%
        45%
        25.7
        BEB33_qc_fHP_1
        24.0%
        49%
        21.4
        BEB33_qc_fHP_2
        27.5%
        49%
        21.4
        BEB34_qc_fHP_1
        17.6%
        52%
        20.0
        BEB34_qc_fHP_2
        19.9%
        52%
        20.0
        BEN02_qc_fHP_1
        41.1%
        47%
        27.9
        BEN02_qc_fHP_2
        41.7%
        47%
        27.9
        BEN04_qc_fHP_1
        23.0%
        46%
        26.1
        BEN04_qc_fHP_2
        23.6%
        46%
        26.1
        BEN05_qc_fHP_1
        22.9%
        45%
        26.2
        BEN05_qc_fHP_2
        24.0%
        45%
        26.2
        BEN07_qc_fHP_1
        17.5%
        46%
        22.3
        BEN07_qc_fHP_2
        18.7%
        46%
        22.3
        BEN08_qc_fHP_1
        26.8%
        45%
        27.4
        BEN08_qc_fHP_2
        28.7%
        45%
        27.4
        BEN09_qc_fHP_1
        18.4%
        47%
        25.8
        BEN09_qc_fHP_2
        19.7%
        47%
        25.8
        BEN10_qc_fHP_1
        45.6%
        46%
        25.1
        BEN10_qc_fHP_2
        50.6%
        46%
        25.1
        BEN11_qc_fHP_1
        22.0%
        45%
        25.6
        BEN11_qc_fHP_2
        26.5%
        45%
        25.6
        BEN12_qc_fHP_1
        28.3%
        46%
        27.2
        BEN12_qc_fHP_2
        33.0%
        46%
        27.2
        BEN13_qc_fHP_1
        18.2%
        45%
        24.9
        BEN13_qc_fHP_2
        23.1%
        45%
        24.9
        BEN14_qc_fHP_1
        16.5%
        45%
        25.4
        BEN14_qc_fHP_2
        19.8%
        45%
        25.4
        BEN16_qc_fHP_1
        28.3%
        46%
        25.7
        BEN16_qc_fHP_2
        31.9%
        46%
        25.7
        BEN17_qc_fHP_1
        19.1%
        45%
        26.5
        BEN17_qc_fHP_2
        22.6%
        45%
        26.5
        BEN18_qc_fHP_1
        24.2%
        45%
        26.5
        BEN18_qc_fHP_2
        28.0%
        45%
        26.5
        BEN19_qc_fHP_1
        25.9%
        44%
        23.0
        BEN19_qc_fHP_2
        28.8%
        44%
        23.0
        BEN20_qc_fHP_1
        18.3%
        46%
        24.5
        BEN20_qc_fHP_2
        22.0%
        46%
        24.5
        BEN21_qc_fHP_1
        17.0%
        45%
        26.4
        BEN21_qc_fHP_2
        19.9%
        45%
        26.4
        BEN22_qc_fHP_1
        20.8%
        46%
        24.3
        BEN22_qc_fHP_2
        24.6%
        46%
        24.3
        BEN23_qc_fHP_1
        30.8%
        46%
        25.7
        BEN23_qc_fHP_2
        34.4%
        46%
        25.7
        BEN24_qc_fHP_1
        22.3%
        46%
        23.8
        BEN24_qc_fHP_2
        25.6%
        46%
        23.8
        BEN26_qc_fHP_1
        14.3%
        49%
        19.9
        BEN26_qc_fHP_2
        17.7%
        49%
        19.9
        BEN27_qc_fHP_1
        32.4%
        47%
        22.9
        BEN27_qc_fHP_2
        37.5%
        47%
        22.9
        BEN28_qc_fHP_1
        13.4%
        46%
        22.7
        BEN28_qc_fHP_2
        17.1%
        46%
        22.7
        BEN29_qc_fHP_1
        45.1%
        47%
        25.0
        BEN29_qc_fHP_2
        49.3%
        47%
        25.0
        BEN30_qc_fHP_1
        26.8%
        46%
        23.3
        BEN30_qc_fHP_2
        31.5%
        46%
        23.3
        BEN31_qc_fHP_1
        20.7%
        47%
        20.8
        BEN31_qc_fHP_2
        24.6%
        47%
        20.8
        BEN32_qc_fHP_1
        20.7%
        45%
        22.9
        BEN32_qc_fHP_2
        25.0%
        45%
        22.9
        BEN33_qc_fHP_1
        17.2%
        46%
        24.6
        BEN33_qc_fHP_2
        21.0%
        46%
        24.6
        BEN34_qc_fHP_1
        10.8%
        49%
        22.2
        BEN34_qc_fHP_2
        13.9%
        49%
        22.2
        BEN35_qc_fHP_1
        38.1%
        43%
        29.0
        BEN35_qc_fHP_2
        42.8%
        43%
        29.0
        BEN36_qc_fHP_1
        20.4%
        45%
        25.1
        BEN36_qc_fHP_2
        24.7%
        46%
        25.1
        BEN37_qc_fHP_1
        17.2%
        45%
        8.4
        BEN37_qc_fHP_2
        22.3%
        45%
        8.4
        BEN38_qc_fHP_1
        19.7%
        46%
        23.7
        BEN38_qc_fHP_2
        25.7%
        46%
        23.7
        BEN39_qc_fHP_1
        12.6%
        47%
        24.0
        BEN39_qc_fHP_2
        16.9%
        47%
        24.0
        BEN40_qc_fHP_1
        16.9%
        46%
        25.3
        BEN40_qc_fHP_2
        21.8%
        46%
        25.3
        BEN41_qc_fHP_1
        24.0%
        46%
        22.9
        BEN41_qc_fHP_2
        29.6%
        46%
        22.9
        BEN42_qc_fHP_1
        24.2%
        44%
        21.5
        BEN42_qc_fHP_2
        30.1%
        44%
        21.5
        BEN43_qc_fHP_1
        15.7%
        47%
        25.4
        BEN43_qc_fHP_2
        20.9%
        47%
        25.4
        BEN44_qc_fHP_1
        26.9%
        46%
        24.8
        BEN44_qc_fHP_2
        30.1%
        46%
        24.8
        BEN45_qc_fHP_1
        15.7%
        48%
        23.1
        BEN45_qc_fHP_2
        18.1%
        48%
        23.1
        BEN46_qc_fHP_1
        34.8%
        46%
        25.2
        BEN46_qc_fHP_2
        37.7%
        46%
        25.2
        BEN47_qc_fHP_1
        17.8%
        47%
        22.7
        BEN47_qc_fHP_2
        20.2%
        47%
        22.7
        BEN49_qc_fHP_1
        17.9%
        47%
        20.8
        BEN49_qc_fHP_2
        20.4%
        47%
        20.8
        BEN50_qc_fHP_1
        18.1%
        44%
        20.7
        BEN50_qc_fHP_2
        22.7%
        44%
        20.7
        BEN51_qc_fHP_1
        19.7%
        44%
        20.6
        BEN51_qc_fHP_2
        24.7%
        44%
        20.6
        BEN52_qc_fHP_1
        26.2%
        45%
        22.5
        BEN52_qc_fHP_2
        31.4%
        45%
        22.5
        BEN53_qc_fHP_1
        18.7%
        46%
        19.0
        BEN53_qc_fHP_2
        23.6%
        46%
        19.0
        BEN54_qc_fHP_1
        20.6%
        45%
        20.9
        BEN54_qc_fHP_2
        25.7%
        45%
        20.9
        BEN55_qc_fHP_1
        10.5%
        47%
        20.0
        BEN55_qc_fHP_2
        14.1%
        47%
        20.0
        BEN56_qc_fHP_1
        10.6%
        47%
        13.1
        BEN56_qc_fHP_2
        11.7%
        47%
        13.1
        BEN57_qc_fHP_1
        17.0%
        46%
        19.2
        BEN57_qc_fHP_2
        18.3%
        46%
        19.2
        BEN58_qc_fHP_1
        15.1%
        47%
        17.5
        BEN58_qc_fHP_2
        16.7%
        47%
        17.5
        BEN60_qc_fHP_1
        27.6%
        45%
        23.3
        BEN60_qc_fHP_2
        29.5%
        45%
        23.3
        BEN61_qc_fHP_1
        19.5%
        45%
        21.5
        BEN61_qc_fHP_2
        20.7%
        45%
        21.5
        BEN62_qc_fHP_1
        18.0%
        48%
        18.1
        BEN62_qc_fHP_2
        20.5%
        48%
        18.1
        BEN63_qc_fHP_1
        17.1%
        45%
        20.8
        BEN63_qc_fHP_2
        19.1%
        45%
        20.8
        BEN64_qc_fHP_1
        25.8%
        46%
        21.0
        BEN64_qc_fHP_2
        28.8%
        46%
        21.0
        BEN65_qc_fHP_1
        16.3%
        48%
        19.7
        BEN65_qc_fHP_2
        18.7%
        48%
        19.7
        BEN66_qc_fHP_1
        18.0%
        45%
        18.1
        BEN66_qc_fHP_2
        20.8%
        45%
        18.1
        BEN69_qc_fHP_1
        26.1%
        45%
        21.2
        BEN69_qc_fHP_2
        28.4%
        45%
        21.2
        BEN70_qc_fHP_1
        12.4%
        47%
        16.8
        BEN70_qc_fHP_2
        14.6%
        47%
        16.8
        BEN71_qc_fHP_1
        30.4%
        46%
        19.9
        BEN71_qc_fHP_2
        32.8%
        46%
        19.9
        BEN72_qc_fHP_1
        13.9%
        49%
        18.8
        BEN72_qc_fHP_2
        16.5%
        49%
        18.8
        BEN73_qc_fHP_1
        18.5%
        46%
        22.2
        BEN73_qc_fHP_2
        20.9%
        46%
        22.2
        BEN74_qc_fHP_1
        26.7%
        45%
        24.5
        BEN74_qc_fHP_2
        29.6%
        45%
        24.5
        BEN75_qc_fHP_1
        19.6%
        44%
        20.1
        BEN75_qc_fHP_2
        22.4%
        44%
        20.1
        BEN76_qc_fHP_1
        13.6%
        43%
        19.4
        BEN76_qc_fHP_2
        18.3%
        43%
        19.4
        BEN77_qc_fHP_1
        20.0%
        44%
        21.9
        BEN77_qc_fHP_2
        25.2%
        44%
        21.9
        BEN78_qc_fHP_1
        28.6%
        45%
        20.7
        BEN78_qc_fHP_2
        34.5%
        45%
        20.7
        BEN80_qc_fHP_1
        23.0%
        44%
        20.2
        BEN80_qc_fHP_2
        29.4%
        45%
        20.2
        BEN81_qc_fHP_1
        16.6%
        45%
        22.1
        BEN81_qc_fHP_2
        21.4%
        46%
        22.1
        BEN82_qc_fHP_1
        31.2%
        45%
        21.7
        BEN82_qc_fHP_2
        37.1%
        45%
        21.7
        BEY01_qc_fHP_1
        18.2%
        47%
        24.8
        BEY01_qc_fHP_2
        19.2%
        47%
        24.8
        BEY02_qc_fHP_1
        29.7%
        48%
        24.6
        BEY02_qc_fHP_2
        30.5%
        48%
        24.6
        BEY03_qc_fHP_1
        22.6%
        47%
        25.2
        BEY03_qc_fHP_2
        23.6%
        47%
        25.2
        BEY04_qc_fHP_1
        18.4%
        49%
        26.6
        BEY04_qc_fHP_2
        19.1%
        49%
        26.6
        BEY05_qc_fHP_1
        32.9%
        49%
        24.7
        BEY05_qc_fHP_2
        35.1%
        49%
        24.7
        BEY06_qc_fHP_1
        28.4%
        45%
        25.3
        BEY06_qc_fHP_2
        29.9%
        45%
        25.3
        BEY07_qc_fHP_1
        17.2%
        51%
        25.9
        BEY07_qc_fHP_2
        19.0%
        51%
        25.9
        BEY08_qc_fHP_1
        20.0%
        48%
        23.7
        BEY08_qc_fHP_2
        21.4%
        48%
        23.7
        BEY09_qc_fHP_1
        14.4%
        51%
        21.8
        BEY09_qc_fHP_2
        19.0%
        51%
        21.8
        BEY10_qc_fHP_1
        13.2%
        53%
        20.7
        BEY10_qc_fHP_2
        18.0%
        53%
        20.7
        BEY11_qc_fHP_1
        27.2%
        49%
        24.5
        BEY11_qc_fHP_2
        32.0%
        50%
        24.5
        BEY12_qc_fHP_1
        25.3%
        50%
        26.6
        BEY12_qc_fHP_2
        31.9%
        50%
        26.6
        BEY13_qc_fHP_1
        24.5%
        44%
        19.4
        BEY13_qc_fHP_2
        29.3%
        44%
        19.4
        BEY14_qc_fHP_1
        23.7%
        46%
        20.7
        BEY14_qc_fHP_2
        28.3%
        46%
        20.7
        BEY15_qc_fHP_1
        21.8%
        45%
        23.8
        BEY15_qc_fHP_2
        27.3%
        45%
        23.8
        BEY16_qc_fHP_1
        20.8%
        47%
        20.2
        BEY16_qc_fHP_2
        25.8%
        47%
        20.2
        BEY17_qc_fHP_1
        29.4%
        44%
        24.3
        BEY17_qc_fHP_2
        34.5%
        44%
        24.3
        BEY18_qc_fHP_1
        34.2%
        44%
        21.7
        BEY18_qc_fHP_2
        39.9%
        44%
        21.7
        BEY19_qc_fHP_1
        15.5%
        47%
        21.2
        BEY19_qc_fHP_2
        18.0%
        47%
        21.2
        BEY20_qc_fHP_1
        18.4%
        45%
        21.0
        BEY20_qc_fHP_2
        20.8%
        45%
        21.0
        BEY21_qc_fHP_1
        24.8%
        46%
        22.8
        BEY21_qc_fHP_2
        27.9%
        46%
        22.8
        BEY22_qc_fHP_1
        22.2%
        47%
        22.2
        BEY22_qc_fHP_2
        25.1%
        47%
        22.2
        BEY23_qc_fHP_1
        18.6%
        46%
        24.0
        BEY23_qc_fHP_2
        21.6%
        46%
        24.0
        BEY24_qc_fHP_1
        16.0%
        49%
        19.1
        BEY24_qc_fHP_2
        18.7%
        49%
        19.1
        BEY25_qc_fHP_1
        17.2%
        47%
        21.3
        BEY25_qc_fHP_2
        20.0%
        47%
        21.3
        BEY26_qc_fHP_1
        17.8%
        53%
        21.3
        BEY26_qc_fHP_2
        20.5%
        53%
        21.3
        BEY27_qc_fHP_1
        14.2%
        48%
        22.1
        BEY27_qc_fHP_2
        18.8%
        49%
        22.1
        BEY28_qc_fHP_1
        18.9%
        52%
        22.0
        BEY28_qc_fHP_2
        25.2%
        52%
        22.0
        BEY29_qc_fHP_1
        13.3%
        50%
        21.7
        BEY29_qc_fHP_2
        18.2%
        50%
        21.7
        BEY30_qc_fHP_1
        14.4%
        51%
        19.8
        BEY30_qc_fHP_2
        18.1%
        51%
        19.8
        BEY31_qc_fHP_1
        10.5%
        50%
        20.0
        BEY31_qc_fHP_2
        14.8%
        50%
        20.0
        BEY32_qc_fHP_1
        21.7%
        46%
        22.5
        BEY32_qc_fHP_2
        27.2%
        47%
        22.5

        FastQC

        FastQC is a quality control tool for high throughput sequence data, written by Simon Andrews at the Babraham Institute in Cambridge.

        Sequence Counts

        Sequence counts for each sample. Duplicate read counts are an estimate only.

        This plot show the total number of reads, broken down into unique and duplicate if possible (only more recent versions of FastQC give duplicate info).

        You can read more about duplicate calculation in the FastQC documentation. A small part has been copied here for convenience:

        Only sequences which first appear in the first 100,000 sequences in each file are analysed. This should be enough to get a good impression for the duplication levels in the whole file. Each sequence is tracked to the end of the file to give a representative count of the overall duplication level.

        The duplication detection requires an exact sequence match over the whole length of the sequence. Any reads over 75bp in length are truncated to 50bp for this analysis.

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        Sequence Quality Histograms

        The mean quality value across each base position in the read.

        To enable multiple samples to be plotted on the same graph, only the mean quality scores are plotted (unlike the box plots seen in FastQC reports).

        Taken from the FastQC help:

        The y-axis on the graph shows the quality scores. The higher the score, the better the base call. The background of the graph divides the y axis into very good quality calls (green), calls of reasonable quality (orange), and calls of poor quality (red). The quality of calls on most platforms will degrade as the run progresses, so it is common to see base calls falling into the orange area towards the end of a read.

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        Per Sequence Quality Scores

        The number of reads with average quality scores. Shows if a subset of reads has poor quality.

        From the FastQC help:

        The per sequence quality score report allows you to see if a subset of your sequences have universally low quality values. It is often the case that a subset of sequences will have universally poor quality, however these should represent only a small percentage of the total sequences.

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        Per Base Sequence Content

        The proportion of each base position for which each of the four normal DNA bases has been called.

        To enable multiple samples to be shown in a single plot, the base composition data is shown as a heatmap. The colours represent the balance between the four bases: an even distribution should give an even muddy brown colour. Hover over the plot to see the percentage of the four bases under the cursor.

        To see the data as a line plot, as in the original FastQC graph, click on a sample track.

        From the FastQC help:

        Per Base Sequence Content plots out the proportion of each base position in a file for which each of the four normal DNA bases has been called.

        In a random library you would expect that there would be little to no difference between the different bases of a sequence run, so the lines in this plot should run parallel with each other. The relative amount of each base should reflect the overall amount of these bases in your genome, but in any case they should not be hugely imbalanced from each other.

        It's worth noting that some types of library will always produce biased sequence composition, normally at the start of the read. Libraries produced by priming using random hexamers (including nearly all RNA-Seq libraries) and those which were fragmented using transposases inherit an intrinsic bias in the positions at which reads start. This bias does not concern an absolute sequence, but instead provides enrichement of a number of different K-mers at the 5' end of the reads. Whilst this is a true technical bias, it isn't something which can be corrected by trimming and in most cases doesn't seem to adversely affect the downstream analysis.

        Click a sample row to see a line plot for that dataset.
        Rollover for sample name
        Position: -
        %T: -
        %C: -
        %A: -
        %G: -

        Per Sequence GC Content

        The average GC content of reads. Normal random library typically have a roughly normal distribution of GC content.

        From the FastQC help:

        This module measures the GC content across the whole length of each sequence in a file and compares it to a modelled normal distribution of GC content.

        In a normal random library you would expect to see a roughly normal distribution of GC content where the central peak corresponds to the overall GC content of the underlying genome. Since we don't know the the GC content of the genome the modal GC content is calculated from the observed data and used to build a reference distribution.

        An unusually shaped distribution could indicate a contaminated library or some other kinds of biased subset. A normal distribution which is shifted indicates some systematic bias which is independent of base position. If there is a systematic bias which creates a shifted normal distribution then this won't be flagged as an error by the module since it doesn't know what your genome's GC content should be.

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        Per Base N Content

        The percentage of base calls at each position for which an N was called.

        From the FastQC help:

        If a sequencer is unable to make a base call with sufficient confidence then it will normally substitute an N rather than a conventional base call. This graph shows the percentage of base calls at each position for which an N was called.

        It's not unusual to see a very low proportion of Ns appearing in a sequence, especially nearer the end of a sequence. However, if this proportion rises above a few percent it suggests that the analysis pipeline was unable to interpret the data well enough to make valid base calls.

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        Sequence Length Distribution

        The distribution of fragment sizes (read lengths) found. See the FastQC help

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        Sequence Duplication Levels

        The relative level of duplication found for every sequence.

        From the FastQC Help:

        In a diverse library most sequences will occur only once in the final set. A low level of duplication may indicate a very high level of coverage of the target sequence, but a high level of duplication is more likely to indicate some kind of enrichment bias (eg PCR over amplification). This graph shows the degree of duplication for every sequence in a library: the relative number of sequences with different degrees of duplication.

        Only sequences which first appear in the first 100,000 sequences in each file are analysed. This should be enough to get a good impression for the duplication levels in the whole file. Each sequence is tracked to the end of the file to give a representative count of the overall duplication level.

        The duplication detection requires an exact sequence match over the whole length of the sequence. Any reads over 75bp in length are truncated to 50bp for this analysis.

        In a properly diverse library most sequences should fall into the far left of the plot in both the red and blue lines. A general level of enrichment, indicating broad oversequencing in the library will tend to flatten the lines, lowering the low end and generally raising other categories. More specific enrichments of subsets, or the presence of low complexity contaminants will tend to produce spikes towards the right of the plot.

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        Overrepresented sequences

        The total amount of overrepresented sequences found in each library.

        FastQC calculates and lists overrepresented sequences in FastQ files. It would not be possible to show this for all samples in a MultiQC report, so instead this plot shows the number of sequences categorized as over represented.

        Sometimes, a single sequence may account for a large number of reads in a dataset. To show this, the bars are split into two: the first shows the overrepresented reads that come from the single most common sequence. The second shows the total count from all remaining overrepresented sequences.

        From the FastQC Help:

        A normal high-throughput library will contain a diverse set of sequences, with no individual sequence making up a tiny fraction of the whole. Finding that a single sequence is very overrepresented in the set either means that it is highly biologically significant, or indicates that the library is contaminated, or not as diverse as you expected.

        FastQC lists all of the sequences which make up more than 0.1% of the total. To conserve memory only sequences which appear in the first 100,000 sequences are tracked to the end of the file. It is therefore possible that a sequence which is overrepresented but doesn't appear at the start of the file for some reason could be missed by this module.

        256 samples had less than 1% of reads made up of overrepresented sequences

        Adapter Content

        The cumulative percentage count of the proportion of your library which has seen each of the adapter sequences at each position.

        Note that only samples with ≥ 0.1% adapter contamination are shown.

        There may be several lines per sample, as one is shown for each adapter detected in the file.

        From the FastQC Help:

        The plot shows a cumulative percentage count of the proportion of your library which has seen each of the adapter sequences at each position. Once a sequence has been seen in a read it is counted as being present right through to the end of the read so the percentages you see will only increase as the read length goes on.

        No samples found with any adapter contamination > 0.1%

        Status Checks

        Status for each FastQC section showing whether results seem entirely normal (green), slightly abnormal (orange) or very unusual (red).

        FastQC assigns a status for each section of the report. These give a quick evaluation of whether the results of the analysis seem entirely normal (green), slightly abnormal (orange) or very unusual (red).

        It is important to stress that although the analysis results appear to give a pass/fail result, these evaluations must be taken in the context of what you expect from your library. A 'normal' sample as far as FastQC is concerned is random and diverse. Some experiments may be expected to produce libraries which are biased in particular ways. You should treat the summary evaluations therefore as pointers to where you should concentrate your attention and understand why your library may not look random and diverse.

        Specific guidance on how to interpret the output of each module can be found in the relevant report section, or in the FastQC help.

        In this heatmap, we summarise all of these into a single heatmap for a quick overview. Note that not all FastQC sections have plots in MultiQC reports, but all status checks are shown in this heatmap.

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        MultiQC v1.14 - Written by Phil Ewels, available on GitHub.

        This report uses HighCharts, jQuery, jQuery UI, Bootstrap, FileSaver.js and clipboard.js.